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Digital technology and SDGs have gained increasing interest from the research community. This chapter aims to explore the field through a holistic review of 188 publications from 2017 to 2022. For the systematic review of 188 articles, a three-step methodology comprising of PRISMA guidelines was performed, bibliometric analysis and text analysis using VOS-Viewer and Sentiment Analysis using RStudio had been undertaken. Bibliographic coupling revealed the following clusters Digital Space (Over all SDG), Localising SDGs, Financial Systems and Growth (SDG 8), Sustainable Supply Chain (SDG 9), Education (SDG 4), Energy Management (SDG 7), Smart Cities (SDG 11 and 13), Gender, Skills, and Responsibility (SDG 5 and 12), Food Management (SDG 1, 2 and 3), Business Innovation (SDG 8 and 9) and ICT (SDG 9). Next, co-occurrence analysis highlighted the following clusters Circular Economy (SDG 8), Higher Education System (SDG 4), Digital health (SDG 3), Industry 4.0 (SDG 9) and Supply Chain Management (SDG 9). Next, text analysis traced the most relevant areas of work within the theme. Finally, sentiment analysis revealed positive sentiments of the field. The research concluded that only a few SDGs had found major focus while the others don't have any solid ground in the literature. This chapter presents a knowledge structure by mapping the most relevant SDGs in the context of digital technology and sets directions for future research.

In terms of countries, renewable energy sources are increasing their importance day by day. The decrease in fossil fuels and the difficulty of accessing the related fuels as well as their expensiveness can be cited as reasons for this situation. This situation obliges countries to make legal arrangements for the production and use of renewable energy sources in their legal systems. In this context, legal arrangements have been made in Turkey regarding the production and use of related energy resources. One of these regulations is the law dated May 10, 2005 and numbered 5346. The relevant law aims to bring electrical energy to the economy in a reliable, economical, and at the same time high quality way by using renewable energy sources. At the same time, the main purposes of enacting the law include increasing the diversity of resources in energy, reducing greenhouse gas emissions as much as possible, evaluating waste, and protecting the environment. At the same time, the law includes sustainable energy sources. It has been defined as nonfossil energy sources such as hydraulic, wind, solar, geothermal, biomass, waves, currents, and tides. In this context, the main purpose of the study is to examine what renewable energy sources are and to reveal the legal nature of energy services by considering the production and use of renewable energy sources in Turkey in the context of Turkish legal legislation.

With numerous and ambiguous sets of information and often conflicting requirements, construction management is a complex process involving much uncertainty. Decision makers may be challenged with satisfying multiple criteria using vague information. Fuzzy multi-criteria decision-making (FMCDM) provides an innovative approach for addressing complex problems featuring diverse decision makers’ interests, conflicting objectives and numerous but uncertain bits of information. FMCDM has therefore been widely applied in construction management. With the increase in information complexity, extensions of fuzzy set (FS) theory have been generated and adopted to improve its capacity to address this complexity. Examples include hesitant FSs (HFSs), intuitionistic FSs (IFSs) and type-2 FSs (T2FSs). This chapter introduces commonly used FMCDM methods, examines their applications in construction management and discusses trends in future research and application. The chapter first introduces the MCDM process as well as FS theory and its three main extensions, namely, HFSs, IFSs and T2FSs. The chapter then explores the linkage between FS theory and its extensions and MCDM approaches. In total, 17 FMCDM methods are reviewed and two FMCDM methods (i.e. T2FS-TOPSIS and T2FS-PROMETHEE) are further improved based on the literature. These 19 FMCDM methods with their corresponding applications in construction management are discussed in a systematic manner. This review and development of FS theory and its extensions should help both researchers and practitioners better understand and handle information uncertainty in complex decision problems.

This research aimed to determine how COVID-19 affected Micro small and medium enterprises’ (MSMEs) participation in sustainable development goals (SDGs) and their adoption of Fin-tech developing nations like India. Involving women in the workforce through microenterprises is crucial to accomplishing the SDGs, and its subsection is focused on decent work and small industries. Data related to knowledge of digital finance was collected using a convenience sample method. Nonetheless, descriptive research was conducted, and although interesting, no definitive findings could be determined. Women entrepreneurs aged between 25 and 35 years provided input into creating this link based on the United Theory of Acceptance and Use of Technology (UTAUT) concept. Using SMART-PLS, we found a significant relationship between the UTAUT model of sustainable development and the level of Fin-tech literacy among women in low-income households in developing countries like India. However, we also know that MSMEs’ adoption of Fin-tech and SDG is less tightly linked to the UTUAT model. The trend towards online transactions or digital payments and the widespread adoption of digital technology applications are changing the face of the global economy. The COVID-19 period saw the rise of contactless transactions as the primary payment method. Because of this shift in public opinion, small- and medium-sized enterprises (SMEs) have begun implementing Fin-tech for long-term growth. People worldwide use it for transactions and other economic functions. However, there is a scarcity of research incorporating this kind of data from India and the rest of the developing world.

Construction is a highly dynamic environment with numerous interacting factors that affect construction processes and decisions. Uncertainty is inherent in most aspects of construction engineering and management, and traditionally, it has been treated as a random phenomenon. However, there are many types of uncertainty that are not naturally modelled by probability theory, such as subjectivity, ambiguity and vagueness. Fuzzy logic provides an approach for handling such uncertainties. However, fuzzy logic alone has some limitations, including its inability to learn from data and its extensive reliance on expert knowledge. To address these limitations, fuzzy logic has been combined with other techniques to create fuzzy hybrid techniques, which have helped solve complex problems in construction. In this chapter, a background on fuzzy logic in the context of construction engineering and management applications is presented. The chapter provides an introduction to uncertainty in construction and illustrates how fuzzy logic can improve construction modelling and decision-making. The role of fuzzy logic in representing uncertainty is contrasted with that of probability theory. Introductory material is presented on key definitions, properties and methods of fuzzy logic, including the definition and representation of fuzzy sets and membership functions, basic operations on fuzzy sets, fuzzy relations and compositions, defuzzification methods, entropy for fuzzy sets, fuzzy numbers, methods for the specification of membership functions and fuzzy rule-based systems. Finally, a discussion on the need for fuzzy hybrid modelling in construction applications is presented, and future research directions are proposed.

Scholarship on workplace diversity, equity, and inclusion (DEI) is voluminous. Nevertheless, there is relatively little work that examines DEI from an organization development and change (ODC) or systems perspective. As a result, there is no unified framework ODC practitioners can use for DEI diagnosis and intervention. The purpose of this chapter is to review the ODC literature with respect to DEI and propose a diagnostic Context-Levels-Culture (CLC) framework for understanding and addressing diversity-related challenges in organizations. We also present a case example of how this framework can be used in DEI consulting, including implications for future research and practice.

The improvement of the agri-food supply chain sustainability plays pivotal role in the planet’s survival and in overcoming of climate disasters. Digital technologies that support the collection of Big Data produced along the agri-food supply chain (SC) emerge as powerful tools to accelerate the ecological transition of the sector. Digital technologies can support the implementation of circular business models by sharing data across the SC, monitoring in real time the materials flow, automatizing some agricultural practices and improving the decision-making through the development of decision support systems. Despite the relevance of these arguments, there is a lack of shared frameworks and guidelines for the effective development of a “data-driven circular economy” in the agri-food SC. In this scenario, this chapter examines how scholars investigate data-oriented strategies to accelerate the ecological transition and the adoption of circular economy (CE) models in the agri-food sector (AFS). To this end, a systematic literature review (SLR) was performed. Twenty-nine papers were selected following a rigorous sampling process. Both bibliometric and descriptive results are provided in the first part of this chapter. According to the analytical framework developed, the selected papers were examined in light of the “reduce, reuse and recycle” (3R) paradigm. Moreover, an additional R was retrieved from the systematic review (i.e., redesign), broadening the analytical perspective. The results indicate that scholars have predominantly provided theoretical contributions concerning the role of digital technologies and big data for the agri-food circular transition from a macro-perspective. The findings are useful for policy-makers and managers, who can promote and implement the big data-oriented approach to facilitate the circular transition. Limitations and future research directions are also provided.